US10901875B2 - Evaluating and presenting software testing project status indicators - Google Patents
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Definitions
- the present disclosure is generally related to computer systems, and is more specifically related to software testing methods and systems.
- Software testing herein shall refer to activity aimed at evaluating certain attributes and/or capabilities of a software program or a software service in order to determine whether the software program or the software service meets certain requirements with respect to its functions, reliability, availability, accuracy, usability, etc.
- FIG. 1 schematically illustrates a high-level network diagram of an example distributed computer system that may implement the methods for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure
- FIGS. 2A-2B schematically illustrate example data visualization graphical user interfaces that may be employed by a computer system implementing the methods described herein for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure
- FIG. 3 schematically illustrates a project schedule mapping certain test execution milestones to planned completion dates, in accordance with one or more aspects of the present disclosure
- FIG. 4 schematically illustrates a table defining an example defect prediction function, in accordance with one or more aspects of the present disclosure
- FIGS. 5A-5B depict a flow diagram of an example method for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure.
- FIG. 6 depicts a block diagram of an illustrative computing device operating in accordance with one or more aspects of the present disclosure.
- Described herein are methods and systems for evaluating and presenting software testing project status indicators.
- a software project may comprise multiple software modules, which may need to be tested separately and/or collectively in various combinations by executing a plurality of testing scenarios.
- Such testing scenarios may be performed at various levels, including unit testing, integration testing, component interface testing, and system testing.
- the testing scenarios may include functional, performance, usability, security, localization, reliability, availability, accuracy, and other types of tests.
- Example 10 “Executed” test herein refers to a test that has been performed, irrespective of the result of such performance (passed or failed).
- “Completed” test herein refers to a passed test.
- Test execution (completion) rate shall refer to the ratio of the number of tests that have been executed (completed) or that are planned to be executed (completed) within a certain period of time to the number of units of time comprised by that time period.
- test execution (completion) rates include: the average test execution (completion) rate over a certain period of time, the required test execution (completion) rate which is needed to achieve a certain project milestone, etc.
- Test execution (completion) ratio refers to the ratio of the number of tests that have been executed as of a certain moment in time or are planned to be executed as of a certain moment in time to the total number of tests to be executed.
- test execution (completion) ratios include: the actual test execution (completion) ratio or a planned test execution (completion) ratio.
- a computer system may determine and present via a graphical user interface various software testing project status indicators, including, e.g., the required test execution rate based on a target completion date, the variance of the actual test execution status with respect to the schedule, and/or an estimated total number of defects to be detected, as described in more details herein below.
- various software testing project status indicators including, e.g., the required test execution rate based on a target completion date, the variance of the actual test execution status with respect to the schedule, and/or an estimated total number of defects to be detected, as described in more details herein below.
- FIG. 1 schematically illustrates a high-level network diagram of an example distributed computer system 1000 , which may implement the methods for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure.
- Computer systems, appliances, and network segments are shown in FIG. 1 for illustrative purposes only and do not in any way limit the scope of the present disclosure.
- Various other computer systems, components, appliances, and/or methods of their interconnection may be compatible with the methods and systems described herein for evaluating and presenting software testing project status indicators.
- Example distributed computer system 1000 may comprise one or more data collection and presentation servers 110 A- 110 Z, which may be configured for implementing the methods for evaluating and presenting software testing project status indicators in accordance with one or more aspects of the present disclosure.
- distributed computer system 1000 may further comprise one or more data storage servers 120 A- 120 Z, which may be configured to store various data related to one or more software testing projects.
- Data storage servers 120 A- 120 Z may be provided by file or block-level storage, relational databases, and/or data storage devices or systems of various other types.
- Example distributed computer system 1000 may further comprise one or more data visualization clients 130 , which may be configured to receive software testing project status indicators from data collection and presentation servers 110 A- 110 Z in order to present the software testing project status indicators via a graphical user interface, as described in more details herein below.
- data visualization clients 130 may be configured to receive software testing project status indicators from data collection and presentation servers 110 A- 110 Z in order to present the software testing project status indicators via a graphical user interface, as described in more details herein below.
- Data collection and presentation servers 110 , data visualization clients 130 , and other components of example distributed computer system 1000 may be interconnected by one or more networks 140 , which may comprise one or more local area networks and/or one or more wide area networks. Firewalls, load balancers, network switches and various other networking components may be omitted from FIG. 1 for clarity.
- one or more data collection and presentation servers 110 and/or other components of example distributed computer system 1000 may be communicatively coupled (e.g., via one or more networks) to one or more software testing hosts (not shown in FIG. 1 ) in order to automatically collect raw data for determining the software testing project status indicators in accordance with one or more aspects of the present disclosure.
- one or more data collection and presentation servers 110 and/or other components of example distributed computer system 1000 may receive at least part of the raw data via a graphical user interface and/or via communication interfaces from other components (not shown in FIG. 1 ) of a software testing system (not shown in FIG. 1 ).
- the raw data may comprise the numbers of executed, passed, and/or failed test cases, the number of defects detected, and other information that may be consumed by data collection and presentation servers 110 in order to determine various software testing project status indicators in accordance with one or more aspects of the present disclosure.
- distributed computer system 1000 serves as an illustrative example only and does not in any way limit the scope of the present disclosure.
- Various other system architectures may be compatible with the methods and systems for determining software testing project status indicators in accordance with one or more aspects of the present disclosure.
- a computer system implementing the methods described herein may receive (e.g., via an application programming interface (API) or via a graphical user interface raw data reflecting certain project parameters, such as the planned project completion date and the total number of test instances to be executed.
- the computer system may then process the received raw data to determine various software testing project status indicators, as described in more details herein below.
- the computer system may then cause the project status indicators to be presented via a user interface (e.g., displayed by one or more data visualization clients 130 ), as described in more details herein below with references to FIGS. 2A-2B .
- the computer system may determine the test execution rate required for meeting a certain project completion date.
- the required test execution rate may be determined as the ratio of the number of test instances to be executed and the number of units of time (e.g., calendar days) remaining until the project completion date.
- the computer system may determine one or more average test execution rates over certain time periods (e.g., a day, a week, a month, etc.), based on raw data comprising the numbers of test instances that were executed within certain time periods.
- the average test execution rate may be determined as the ratio of the number of executed tests within a certain period time and the number of units of time (e.g., calendar days) comprised by that period of time.
- the computer system may determine the current test pass ratio being equal to the ratio of the number of passed test instances to the total number of executed test instances.
- the computer system may determine the test execution schedule variance, which is represented by the number of units of time (e.g., calendar days) between the date corresponding to the actual test execution ratio (e.g., reflected by a ratio of the number of actually executed tests to the total number of tests) and the date, for which the schedule variance is being determined.
- the schedule variance may be determined using a project timeline, which maps a plurality of values of the expected test execution ratio (i.e., the ratio of the number of tests to be executed by a certain date to the total number of tests to be executed) to a plurality of calendar dates.
- the project timeline may be defined by a set of milestones, in which each milestone defines a date, by which a certain test execution ratio is planned to be achieved.
- the expected test execution ratio for other calendar periods i.e., calendar dates between two milestone dates
- FIG. 3 schematically illustrates a project schedule mapping certain test execution milestones to planned completion dates, in accordance with one or more aspects of the present disclosure.
- a set 310 of milestones comprises a plurality of mappings of certain project milestones (25%, 50%, 75%, and 100% of tests being executed) to planned completion dates.
- the computer system may use milestone set 310 for producing a project timeline 320 , by interpolating the values of the expected test execution ratios for calendar dates that do not coincide with the milestone dates.
- FIG. 3 schematically illustrates a project schedule mapping certain test execution milestones to planned completion dates, in accordance with one or more aspects of the present disclosure.
- a set 310 of milestones comprises a plurality of mappings of certain project milestones (25%, 50%, 75%, and 100% of tests being executed) to planned completion dates.
- the computer system may use milestone set 310 for producing a project timeline 320 , by interpolating the values of the expected test execution ratios for calendar dates that do not coincide with the milestone dates.
- the computer system may perform a linear interpolation based on the defined values of test execution ratios for two milestone dates are closest to the calendar date, for which the test execution ratio needs to be determined.
- a computer system implementing the methods described herein may use the project timeline for determining the test execution schedule variance.
- the test execution schedule variance may be determined as the number of units of time (e.g., calendar days) between the date corresponding to the actual test execution ratio and the date for which the schedule variance is being determined. In an illustrative example of FIG. 3 , on July 29, the actual test execution ratio was equal to 63.1%, and hence the test execution schedule variance as of July 29 is determined as the number of calendar days between July 29 and July 23, which is the date corresponding to the actual test execution ratio of 63.1%.
- the computer system may cause the test execution schedule variance to be presented via a user interface (e.g., displayed by one or more data visualization clients 130 ), as described in more details herein below with reference to FIG. 2B .
- the computer system may determine the test completion schedule variance, which is represented by the number of units of time (e.g., calendar days) between the date corresponding to the actual test completion ratio and the date for which the schedule variance is being determined.
- the schedule variance may be determined using a project timeline, which shows the expected test completion ratio (i.e., the ratio of the number of tests to be completed by a certain date to the total number of tests to be completed) for a plurality of calendar dates.
- the project timeline may be defined by a set of milestones, in which each milestone defines a date by which a certain test completion ratio is planned to be achieved.
- the expected test completion ratio for other calendar periods i.e., calendar dates between two milestone dates
- the computer system may cause a plurality of software testing project status indicators to be presented via a user interface (e.g., displayed by one or more data visualization clients 130 ) in a visual relation to each other, to a timeline, and/or to another project's status indicators.
- the project status indicators may include one or more average test execution rates, the required test execution rate, the test execution schedule variance, the actual test completion ratio, and/or the test completion schedule variance.
- the visual relation may be provided by the relative placement of the values of the project status indicators, by displaying certain graphical elements that are visually linking the values of the project status indicators, and/or by using a certain color palette for displaying the values of the project status indicators.
- FIGS. 2A-2B schematically illustrate example data visualization graphical user interfaces that may be employed by a computer system implementing the methods described herein for evaluating and presenting software testing project status indicators.
- example data presentation screen 200 A comprises several numerical output fields representing the current values of certain project status indicators, including an output field 210 representing the required test execution rate determined based on a certain project completion date, an output field 212 representing the current value of the 7-day average test execution date, and an output field 214 representing the current value of the 30-day average test execution date.
- Example data presentation screen 200 A further comprises several graphs depicting varying values of certain project status indicators over a certain time period, including a bar chart 216 depicting the numbers of tests that were executed by calendar day, a graph 218 depicting the 7-day average test execution date by calendar day, and a graph 220 depicting the 30-day average test execution date by calendar day.
- Example data presentation screen 200 B comprises a table 228 , rows of which correspond to projects, and the columns define, respectively, the project title or other identifier (column 230 ), the current test pass ratio (column 232 ), the actual test execution ratio (column 234 ), the current test execution schedule variance (column 236 ), the actual test completion ratio (column 238 ), and the current test completion schedule variance (column 240 ).
- a computer system implementing the methods described herein may further determine an estimated total number of defects to be detected. Based on the estimated total number of defects and the actual test execution ratio, the computer system may further determine an estimated number of remaining defects to be detected as of a certain date.
- the estimated total number of defects may be determined using a defect prediction function, which maps a plurality of values of the test completion ratio to a plurality of values of the defect detection ratio.
- the defect prediction function may be defined by a table, as schematically illustrated by FIG. 4 .
- Table 400 may comprise a plurality of entries 410 , such that each entry 410 associates a test execution ratio (i.e., the ratio of the number of executed tests to the total number of tests to be executed) with a corresponding defect detection ratio.
- the defect prediction table may be created based on an experimental data set comprising a plurality of data items relating to a plurality of previously performed software testing projects. Each data item of the experimental data set may correlate a value of the defect detection ratio to a value of the test execution ratio.
- D is the estimated total number of defects to be detected
- A is the actual number of detected defects.
- the defect detection ratio C corresponding to the actual test completion ratio may be determined using the defect prediction table.
- the computer system may cause the estimated total number of defects to be detected, the estimated number of remaining defects to be detected as of a certain date, and certain other project parameters to be presented via a user interface (e.g., displayed by one or more data visualization clients 130 ).
- FIG. 5A depicts a flow diagram of an illustrative example of method 500 A for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure.
- Method 500 A and/or each of its individual functions, routines, subroutines, or operations may be performed by one or more computer systems comprising one or more general purpose and/or specialized processors. Two or more functions, routines, subroutines, or operations of method 500 A may be performed in parallel or in an order that may differ from the order described above.
- method 500 A may be performed by a single processing thread.
- method 500 A may be performed by two or more processing threads, each thread executing one or more individual functions, routines, subroutines, or operations of the method.
- the processing threads implementing method 500 A may be synchronized (e.g., using semaphores, critical sections, and/or other thread synchronization mechanisms). Alternatively, the processing threads implementing method 500 A may be executed asynchronously with respect to each other. In an illustrative example, method 500 A may be performed by an example computer system 600 described herein below with references to FIG. 6 .
- the computer system implementing the method may determine a required test execution rate based on a target completion date.
- the required test execution rate may be determined as the ratio of the number of test instances to be executed to the number of units of time (e.g., calendar days) remaining until the project completion date, as described in more details herein above.
- the computer system may determine an average test execution rate over a certain period of time (e.g., a day, a week, a month, etc.), based on raw data comprising the numbers of test instances that were executed within certain time periods.
- the average test execution rate may be determined as the ratio of the number of executed tests within a certain period time and the number of units of time (e.g., calendar days) comprised by that period of time, as described in more details herein above.
- the computer system may determine the actual test execution ratio as the ratio of the number of executed test instances to the total number of test instances to be executed, as described in more details herein above.
- the computer system may determine the test execution schedule variance as the number of units of time (e.g., calendar days) between the date corresponding to the actual test execution ratio and the date for which the schedule variance is being determined, as described in more details herein above.
- the computer system may determine the actual test completion ratio as the ratio of the number of completed test instances to the total number of test instances to be executed, as described in more details herein above.
- the computer system may determine the test completion schedule variance as the number of units of time (e.g., calendar days) between the date corresponding to the actual test completion ratio and the date for which the schedule variance is being determined, as described in more details herein above.
- the computer system may cause a plurality of software testing project status indicators to be presented via a user interface in a visual relation to each other, to a timeline, and/or to another project's status indicators.
- the project status indicators may include one or more average test execution rates, the required test execution rate, the test execution schedule variance, the actual test completion ratio, and/or the test completion schedule variance.
- the visual relation between the displayed values may be provided by the relative placement of the values on the screen, by displaying certain graphical elements that are visually linking the values of average test execution rates and the value of the required test execution rate on the screen, and/or by using a certain color palette for displaying the values of average test execution rates and the value of the required test execution rate on the screen, as described in more details herein above.
- FIG. 5B depicts a flow diagram of an illustrative example of method 500 B for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure.
- Method 500 B and/or each of its individual functions, routines, subroutines, or operations may be performed by one or more computer systems comprising one or more general purpose and/or specialized processors. Two or more functions, routines, subroutines, or operations of method 500 B may be performed in parallel or in an order that may differ from the order described above.
- method 500 B may be performed by a single processing thread.
- method 500 B may be performed by two or more processing threads, each thread executing one or more individual functions, routines, subroutines, or operations of the method.
- the processing threads implementing method 500 B may be synchronized (e.g., using semaphores, critical sections, and/or other thread synchronization mechanisms). Alternatively, the processing threads implementing method 500 B may be executed asynchronously with respect to each other. In an illustrative example, method 500 B may be performed by an example computer system 600 described herein below with references to FIG. 6 .
- the computer system implementing the method may create, based on one or more experimental data items, a defect prediction table comprising a plurality of entries, each entry associating a certain defect detection ratio with the test execution ratio, as described in more details herein above.
- the computer system may determine, using the defect prediction table, a value of the defect detection ratio corresponding to a given test execution ratio, as described in more details herein above.
- the computer system may determine an estimated total number of defects to be detected based on the defect detection ratio and a given actual number of detected defects, as described in more details herein above.
- the computer system may determine an estimated number of remaining defects to be detected as the difference between the estimated total number of defects and the actual number of detected defects, as described in more details herein above.
- the computer system may cause a plurality of software testing project status indicators to be presented via a user interface in a visual relation to each other, to a timeline, and/or to another project's status indicators.
- the project status indicators may include the estimated total number of defects to be detected and/or the number of the remaining defects.
- the visual relation between the displayed values may be provided by the relative placement of the values on the screen, by displaying certain graphical elements that are visually linking the values of average test execution rates and the value of the required test execution rate on the screen, and/or by using a certain color palette for displaying the values of average test execution rates and the value of the required test execution rate on the screen, as described in more details herein above.
- FIG. 6 illustrates a diagrammatic representation of an example computer system 600 , within which a set of instructions for causing the computing device to perform the methods described herein may be executed.
- Computer system 600 may be connected to other computing devices in a LAN, an intranet, an extranet, and/or the Internet.
- Computer system 600 may operate in the capacity of a server machine in client-server network environment.
- Computer system 600 may be provided by a personal computer (PC), a set-top box (STB), a server, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine.
- PC personal computer
- STB set-top box
- server a server
- network router switch or bridge
- computer system 600 may implement the above described methods 500 A- 500 B for evaluating and presenting software testing project status indicators.
- Computer system 600 may include a processing device (e.g., a general purpose processor) 1002 , a main memory 1004 (e.g., synchronous dynamic random access memory (DRAM), read-only memory (ROM)), a static memory 1006 (e.g., flash memory and a data storage device 1018 ), which may communicate with each other via a bus 1030 .
- a processing device e.g., a general purpose processor
- main memory 1004 e.g., synchronous dynamic random access memory (DRAM), read-only memory (ROM)
- static memory 1006 e.g., flash memory and a data storage device 1018
- Processing device 1002 may be provided by one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like.
- processing device 1002 may comprise a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, or a processor implementing other instruction sets or processors implementing a combination of instruction sets.
- Processing device 1002 may also comprise one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like.
- the processing device 1002 may be configured to execute methods 500 A- 500 B for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure.
- Computer system 600 may further include a network interface device 1008 , which may communicate with a network 1020 .
- Computer system 600 also may include a video display unit 1010 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)), an alphanumeric input device 1012 (e.g., a keyboard), a cursor control device 1014 (e.g., a mouse) and an acoustic signal generation device 1016 (e.g., a speaker).
- video display unit 1010 , alphanumeric input device 1012 , and cursor control device 1014 may be combined into a single component or device (e.g., an LCD touch screen).
- Data storage device 1018 may include a computer-readable storage medium 1028 , on which may be stored one or more sets of instructions (e.g., instructions of methods 500 A- 500 B for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure) implementing any one or more of the methods or functions described herein. Instructions implementing methods 500 A- 500 B may also reside, completely or at least partially, within main memory 1004 and/or within processing device 1002 during execution thereof by computer system 600 , main memory 1004 and processing device 1002 also constituting computer-readable media. The instructions may further be transmitted or received over network 1020 via network interface device 1008 .
- instructions e.g., instructions of methods 500 A- 500 B for evaluating and presenting software testing project status indicators, in accordance with one or more aspects of the present disclosure
- Instructions implementing methods 500 A- 500 B may also reside, completely or at least partially, within main memory 1004 and/or within processing device 1002 during execution thereof by computer system 600 , main memory 1004 and processing device
- While computer-readable storage medium 1028 is shown in an illustrative example to be a single medium, the term “computer-readable storage medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database and/or associated caches and servers) that store the one or more sets of instructions.
- the term “computer-readable storage medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform the methods described herein.
- the term “computer-readable storage medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical media and magnetic media.
- terms such as “updating,” “identifying,” “determining,” “sending,” “assigning,” or the like refer to actions and processes performed or implemented by computing devices that manipulate and transform data represented as physical (electronic) quantities within the computing device's registers and memories into other data similarly represented as physical quantities within the computing device memories or registers or other such information storage, transmission or display devices.
- the terms “first,” “second,” “third,” “fourth,” etc. as used herein are meant as labels to distinguish among different elements and may not necessarily have an ordinal meaning according to their numerical designation.
- Examples described herein also relate to an apparatus for performing the methods described herein.
- This apparatus may be specially constructed for the required purposes, or it may comprise a general purpose computing device selectively programmed by a computer program stored in the computing device.
- a computer program may be stored in a computer-readable non-transitory storage medium.
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US20190377665A1 (en) | 2019-12-12 |
US20160275006A1 (en) | 2016-09-22 |
US10437707B2 (en) | 2019-10-08 |
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